IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v123y2020i2d10.1007_s11192-020-03412-w.html
   My bibliography  Save this article

An exploration of gender gap using advanced data science tools: actuarial research community

Author

Listed:
  • Mengyu Yu

    (Miami University)

  • Mazie Krehbiel

    (Miami University)

  • Samantha Thompson

    (Miami University)

  • Tatjana Miljkovic

    (Miami University)

Abstract

This paper explores the role of gender gap in the actuarial research community with advanced data science tools. The web scraping tools were employed to create a database of publications that encompasses six major actuarial journals. This database includes the article names, authors’ names, publication year, volume, and the number of citations for the time period 2005–2018. The advanced tools built as part of the R software were used to perform gender classification based on the author’s name. Further, we developed a social network analysis by gender in order to analyze the collaborative structure and other forms of interaction within the actuarial research community. A Poisson mixture model was used to identify major clusters with respect to the frequency of citations by gender across the six journals. The analysis showed that women’s publishing and citation networks are more isolated and have fewer ties than male networks. The paper contributes to the broader literature on the “Matthew effect” in academia. We hope that our study will improve understanding of the gender gap within the actuarial research community and initiate a discussion that will lead to developing strategies for a more diverse, inclusive, and equitable community.

Suggested Citation

  • Mengyu Yu & Mazie Krehbiel & Samantha Thompson & Tatjana Miljkovic, 2020. "An exploration of gender gap using advanced data science tools: actuarial research community," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(2), pages 767-789, May.
    • Handle: RePEc:spr:scient:v:123:y:2020:i:2:d:10.1007_s11192-020-03412-w
    DOI: 10.1007/s11192-020-03412-w
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-020-03412-w
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-020-03412-w?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jevin D West & Jennifer Jacquet & Molly M King & Shelley J Correll & Carl T Bergstrom, 2013. "The Role of Gender in Scholarly Authorship," PLOS ONE, Public Library of Science, vol. 8(7), pages 1-6, July.
    2. Garrido, J. & Genest, C. & Schulz, J., 2016. "Generalized linear models for dependent frequency and severity of insurance claims," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 205-215.
    3. Olesia Iefremova & Kamil Wais & Marcin Kozak, 2018. "Biographical articles in scientific literature: analysis of articles indexed in Web of Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(3), pages 1695-1719, December.
    4. Dion, Michelle L. & Sumner, Jane Lawrence & Mitchell, Sara McLaughlin, 2018. "Gendered Citation Patterns across Political Science and Social Science Methodology Fields," Political Analysis, Cambridge University Press, vol. 26(3), pages 312-327, July.
    5. Helena Mihaljević-Brandt & Lucía Santamaría & Marco Tullney, 2016. "The Effect of Gender in the Publication Patterns in Mathematics," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-23, October.
    6. Chad M Topaz & Shilad Sen, 2016. "Gender Representation on Journal Editorial Boards in the Mathematical Sciences," PLOS ONE, Public Library of Science, vol. 11(8), pages 1-21, August.
    7. L. Lee Colquitt & David W. Sommer & William L. Ferguson, 2009. "A Citation Analysis of Risk, Insurance, and Actuarial Research: 2001 Through 2005," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 76(4), pages 933-953, December.
    8. Christian Genest & Alberto Carabarín-Aguirre, 2013. "A Digital Picture of the Actuarial Research Community," North American Actuarial Journal, Taylor & Francis Journals, vol. 17(1), pages 3-12.
    9. Shi, Peng & Feng, Xiaoping & Ivantsova, Anastasia, 2015. "Dependent frequency–severity modeling of insurance claims," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 417-428.
    10. Tatjana Miljkovic & Daniel Fernández, 2018. "On Two Mixture-Based Clustering Approaches Used in Modeling an Insurance Portfolio," Risks, MDPI, vol. 6(2), pages 1-18, May.
    11. Luke Holman & Devi Stuart-Fox & Cindy E Hauser, 2018. "The gender gap in science: How long until women are equally represented?," PLOS Biology, Public Library of Science, vol. 16(4), pages 1-20, April.
    12. repec:nas:journl:v:115:y:2018:p:4887-4890 is not listed on IDEAS
    13. Leisch, Friedrich, 2004. "FlexMix: A General Framework for Finite Mixture Models and Latent Class Regression in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 11(i08).
    14. Kevin W. Boyack & Henry Small & Richard Klavans, 2013. "Improving the accuracy of co‐citation clustering using full text," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(9), pages 1759-1767, September.
    15. Grün, Bettina & Leisch, Friedrich, 2008. "FlexMix Version 2: Finite Mixtures with Concomitant Variables and Varying and Constant Parameters," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 28(i04).
    16. Kevin W. Boyack & Henry Small & Richard Klavans, 2013. "Improving the accuracy of co-citation clustering using full text," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(9), pages 1759-1767, September.
    17. Rørstad, Kristoffer & Aksnes, Dag W., 2015. "Publication rate expressed by age, gender and academic position – A large-scale analysis of Norwegian academic staff," Journal of Informetrics, Elsevier, vol. 9(2), pages 317-333.
    18. L. Lee Colquitt, 2003. "An Analysis of Risk, Insurance, and Actuarial Research: Citations From 1996 to 2000," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 70(2), pages 315-338, June.
    19. Butts, Carter T., 2008. "network: A Package for Managing Relational Data in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 24(i02).
    20. Ding, Ying, 2011. "Scientific collaboration and endorsement: Network analysis of coauthorship and citation networks," Journal of Informetrics, Elsevier, vol. 5(1), pages 187-203.
    21. Brown, Garfield O. & Buckley, Winston S., 2015. "Experience rating with Poisson mixtures," Annals of Actuarial Science, Cambridge University Press, vol. 9(2), pages 304-321, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gregorio González-Alcaide, 2021. "Bibliometric studies outside the information science and library science field: uncontainable or uncontrollable?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 6837-6870, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lin Zhang & Yuanyuan Shang & Ying Huang & Gunnar Sivertsen, 2022. "Gender differences among active reviewers: an investigation based on publons," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 145-179, January.
    2. Zhang, Lin & Shang, Yuanyuan & HUANG, Ying & Sivertsen, Gunnar, 2021. "Gender differences among active reviewers: an investigation based on Publons," SocArXiv 4z6w8, Center for Open Science.
    3. Verschuren, Robert Matthijs, 2022. "Frequency-severity experience rating based on latent Markovian risk profiles," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 379-392.
    4. Josh Yamamoto & Eitan Frachtenberg, 2022. "Gender Differences in Collaboration Patterns in Computer Science," Publications, MDPI, vol. 10(1), pages 1-21, February.
    5. Fengyuan Liu & Petter Holme & Matteo Chiesa & Bedoor AlShebli & Talal Rahwan, 2023. "Gender inequality and self-publication are common among academic editors," Nature Human Behaviour, Nature, vol. 7(3), pages 353-364, March.
    6. Mike Thelwall, 2020. "Female citation impact superiority 1996–2018 in six out of seven English‐speaking nations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 71(8), pages 979-990, August.
    7. Hamid R. Jamali & Alireza Abbasi, 2023. "Gender gaps in Australian research publishing, citation and co-authorship," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(5), pages 2879-2893, May.
    8. Nakajima, Kazuki & Liu, Ruodan & Shudo, Kazuyuki & Masuda, Naoki, 2023. "Quantifying gender imbalance in East Asian academia: Research career and citation practice," Journal of Informetrics, Elsevier, vol. 17(4).
    9. Parminder Bakshi-Hamm & Andreas Hamm, 2022. "Knowledge Production: Analysing Gender- and Country-Dependent Factors in Research Topics through Term Communities," Publications, MDPI, vol. 10(4), pages 1-37, November.
    10. Julie Fortin & Bjarne Bartlett & Michael Kantar & Michelle Tseng & Zia Mehrabi, 2021. "Digital technology helps remove gender bias in academia," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4073-4081, May.
    11. Ho Fai Chan & Benno Torgler, 2020. "Gender differences in performance of top cited scientists by field and country," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2421-2447, December.
    12. Christian Kleiber & Achim Zeileis, 2016. "Visualizing Count Data Regressions Using Rootograms," The American Statistician, Taylor & Francis Journals, vol. 70(3), pages 296-303, July.
    13. Lebret, Rémi & Iovleff, Serge & Langrognet, Florent & Biernacki, Christophe & Celeux, Gilles & Govaert, Gérard, 2015. "Rmixmod: The R Package of the Model-Based Unsupervised, Supervised, and Semi-Supervised Classification Mixmod Library," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i06).
    14. Ramon Alemany & Catalina Bolancé & Roberto Rodrigo & Raluca Vernic, 2020. "Bivariate Mixed Poisson and Normal Generalised Linear Models with Sarmanov Dependence—An Application to Model Claim Frequency and Optimal Transformed Average Severity," Mathematics, MDPI, vol. 9(1), pages 1-18, December.
    15. Grün, Bettina & Kosmidis, Ioannis & Zeileis, Achim, 2012. "Extended Beta Regression in R: Shaken, Stirred, Mixed, and Partitioned," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i11).
    16. Kwiek, Marek & Roszka, Wojciech, 2021. "Gender-based homophily in research: A large-scale study of man-woman collaboration," Journal of Informetrics, Elsevier, vol. 15(3).
    17. Kwiek, Marek & Szymula, Łukasz, 2024. "Growth of Science and Women: Methodological Challenges of Using Structured Big Data," SocArXiv w34pr, Center for Open Science.
    18. Dangzhi Zhao & Andreas Strotmann, 2020. "Telescopic and panoramic views of library and information science research 2011–2018: a comparison of four weighting schemes for author co-citation analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(1), pages 255-270, July.
    19. Marc A. Scott & Kaushik Mohan & Jacques‐Antoine Gauthier, 2020. "Model‐based clustering and analysis of life history data," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(3), pages 1231-1251, June.
    20. Michele Pezzoni & Fabiana Visentin, 2024. "Gender bias in team formation: the case of the European Science Foundation’s grants," Science and Public Policy, Oxford University Press, vol. 51(2), pages 247-260.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:123:y:2020:i:2:d:10.1007_s11192-020-03412-w. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.